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      Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives

      research-article
      1 , , 2 , 3 , 4 , 4 , 5 , 6 , 7 , 8 , 4 , 9 , 10 , 11 , 12 , 13 , 14 , 4 , 12 , 15 , 16 , 17 , 1 , 12 , 18 , 6 , 19 , 20 , 12 , 4 , 21 , 11 , 4 , 22 , 2 , 23 , 13 , 24 , 2
      Reviews of Geophysics (Washington, D.C. : 1985)
      John Wiley and Sons Inc.
      cloud droplet concentrations, satellite, radar, lidar, remote sensing, passive retrievals

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          Abstract

          The cloud droplet number concentration ( N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth ( τ c) cloud droplet effective radius ( r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined.

          Key Points

          • Satellite cloud droplet concentration uncertainties of 78% for pixel‐level retrievals and 54% for 1 by 1 degree retrievals are estimated

          • The effective radius retrieval is the most important aspect for improvement, and more in situ evaluation is needed

          • Potential improvements using passive and active satellite, and ground‐based instruments are discussed

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          Most cited references214

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          The MODIS Aerosol Algorithm, Products, and Validation

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            Global indirect aerosol effects: a review

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              Pollution and the planetary albedo

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                Author and article information

                Contributors
                daniel.p.grosvenor@gmail.com
                Journal
                Rev Geophys
                Rev Geophys
                10.1002/(ISSN)1944-9208
                ROG
                Reviews of Geophysics (Washington, D.C. : 1985)
                John Wiley and Sons Inc. (Hoboken )
                8755-1209
                27 June 2018
                June 2018
                : 56
                : 2 ( doiID: 10.1002/rog.v56.2 )
                : 409-453
                Affiliations
                [ 1 ] School of Earth and Environment University of Leeds Leeds UK
                [ 2 ] Leipzig Institute for Meteorology Universität Leipzig Leipzig Germany
                [ 3 ] Department of Atmospheric Sciences Rosenstiel School of Marine and Atmospheric Science Miami FL USA
                [ 4 ] NASA Goddard Institute for Space Studies New York NY USA
                [ 5 ] Department of Applied Physics and Applied Mathematics Columbia University New York NY USA
                [ 6 ] Department of Earth and Environmental Sciences Vanderbilt University Nashville TN USA
                [ 7 ] Space Science and Engineering Center University of Wisconsin‐Madison Madison WI USA
                [ 8 ] Royal Netherlands Meteorological Institute De Bilt The Netherlands
                [ 9 ] Department of Atmospheric Science Colorado State University Fort Collins CO USA
                [ 10 ] Rutherford Appleton Laboratory Harwell UK
                [ 11 ] Department of Physics University of Oxford Oxford UK
                [ 12 ] Leibniz Institute for Tropospheric Research Leipzig Germany
                [ 13 ] Department of Atmospheric Sciences University of Washington Seattle WA USA
                [ 14 ] Chemical Sciences Division, Earth System Research Laboratory National Oceanic and Atmospheric Administration Boulder CO USA
                [ 15 ] Deutscher Wetterdienst Lindenberg Germany
                [ 16 ] School of Marine and Atmospheric Sciences Stony Brook University Stony Brook NY USA
                [ 17 ] NASA Goddard Space Flight Center Greenbelt MD USA
                [ 18 ] NASA Langley Research Center Hampton VA USA
                [ 19 ] Institute of Earth Sciences The Hebrew University of Jerusalem Jerusalem Israel
                [ 20 ] Department of Geoscience and Remote Sensing Delft University of Technology Delft The Netherlands
                [ 21 ] Department of Earth and Environmental Engineering Columbia University New York NY USA
                [ 22 ] Center for Climate Systems Research Columbia University New York NY USA
                [ 23 ] Joint Center for Earth Systems Technology Baltimore MD USA
                [ 24 ] Physics Department UMBC Baltimore MD USA
                Author notes
                [*] [* ] Correspondence to: D. P. Grosvenor,

                daniel.p.grosvenor@ 123456gmail.com

                Author information
                http://orcid.org/0000-0002-4919-7751
                http://orcid.org/0000-0003-4719-372X
                http://orcid.org/0000-0003-0254-6253
                http://orcid.org/0000-0003-4894-8434
                http://orcid.org/0000-0002-8951-6913
                http://orcid.org/0000-0003-2147-5921
                http://orcid.org/0000-0002-0774-2926
                http://orcid.org/0000-0002-9020-0852
                http://orcid.org/0000-0002-5984-7869
                http://orcid.org/0000-0002-3973-1359
                http://orcid.org/0000-0002-1281-4672
                http://orcid.org/0000-0002-0784-7656
                http://orcid.org/0000-0002-5626-3761
                http://orcid.org/0000-0002-1191-0128
                http://orcid.org/0000-0001-5622-8619
                http://orcid.org/0000-0002-4652-5561
                http://orcid.org/0000-0002-7141-0934
                http://orcid.org/0000-0002-1401-3828
                http://orcid.org/0000-0001-9491-1654
                http://orcid.org/0000-0001-7057-194X
                Article
                ROG20163 10.1029/2017RG000593
                10.1029/2017RG000593
                6099364
                30148283
                37d404b8-96c7-4f75-af1b-90fd794417c8
                ©2018. The Authors.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 December 2017
                : 05 April 2018
                : 06 April 2018
                Page count
                Figures: 0, Tables: 0, Pages: 45, Words: 24277
                Funding
                Funded by: University of Leeds
                Funded by: ACSIS
                Funded by: Federal Ministry for Education and Research in Germany (BMBF)
                Award ID: FKZ 01LK1503A
                Award ID: 01LK1505E
                Funded by: European Research Council (ERC)
                Award ID: 306284
                Award ID: 724602
                Funded by: NASA
                Award ID: NNX14AJ25G
                Award ID: NNX15AC77G
                Funded by: PRIMAVERA
                Funded by: European Union's Horizon 2020
                Award ID: 641727
                Funded by: U.S. Department of Energy Office of Science
                Award ID: DE-SC0016237
                Funded by: NASA Radiation Sciences Program
                Award ID: NNX15AF98G
                Categories
                Atmospheric Composition and Structure
                Cloud Physics and Chemistry
                Cloud/Radiation Interaction
                Atmospheric Processes
                Clouds and Aerosols
                Remote Sensing
                Instruments and Techniques
                Natural Hazards
                Remote Sensing and Disasters
                Review Article
                Review Articles
                Custom metadata
                2.0
                rog20163
                rog20163-hdr-0001
                June 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.4 mode:remove_FC converted:20.08.2018

                cloud droplet concentrations,satellite,radar,lidar,remote sensing,passive retrievals

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